WGCNA: an R package for weighted correlation network analysis
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# Settings
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# Display the current working directory
#getwd();
# If necessary, change the path below to the directory where the data files are stored.
# "." means current directory. On Windows use a forward slash / instead of the usual \.
#workingDir = "./data";
#setwd(workingDir);
library(WGCNA)
## Loading required package: dynamicTreeCut
## Loading required package: fastcluster
##
## Attaching package: 'fastcluster'
## The following object is masked from 'package:stats':
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## hclust
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##
## Attaching package: 'WGCNA'
## The following object is masked from 'package:stats':
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## cor
enableWGCNAThreads()
## Allowing parallel execution with up to 7 working processes.
# Load the data saved in the first part
lnames = load(file = "FemaleLiver-01-dataInput.RData");
#The variable lnames contains the names of loaded variables.
#lnames
## pickSoftThreshold: will use block size 3600.
## pickSoftThreshold: calculating connectivity for given powers...
## ..working on genes 1 through 3600 of 3600
## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.0278 0.345 0.456 747.00 762.0000 1210.0
## 2 2 0.1260 -0.597 0.843 254.00 251.0000 574.0
## 3 3 0.3400 -1.030 0.972 111.00 102.0000 324.0
## 4 4 0.5060 -1.420 0.973 56.50 47.2000 202.0
## 5 5 0.6810 -1.720 0.940 32.20 25.1000 134.0
## 6 6 0.9020 -1.500 0.962 19.90 14.5000 94.8
## 7 7 0.9210 -1.670 0.917 13.20 8.6800 84.1
## 8 8 0.9040 -1.720 0.876 9.25 5.3900 76.3
## 9 9 0.8590 -1.700 0.836 6.80 3.5600 70.5
## 10 10 0.8330 -1.660 0.831 5.19 2.3800 65.8
## 11 12 0.8530 -1.480 0.911 3.33 1.1500 58.1
## 12 14 0.8760 -1.380 0.949 2.35 0.5740 51.9
## 13 16 0.9070 -1.300 0.970 1.77 0.3090 46.8
## 14 18 0.9120 -1.240 0.973 1.39 0.1670 42.5
## 15 20 0.9310 -1.210 0.977 1.14 0.0951 38.7